Principal Applied Scientist

Key Skills

AWS, Design, Docker, Effective communication skills, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

Unlikely AI is a deep tech startup working to create a world where highly intelligent automated systems enable humanity to flourish and benefit us all. We are pioneering transformative technology aimed at making Artificial Intelligence more accurate, trustworthy and safe. By taking a contrarian approach, we believe our technology can solve some of the most pressing problems facing the industry. Based in London, the company was founded by William Tunstall-Pedoe, best known for his key role in the creation of Alexa following the acquisition of his first start-up by Amazon in 2012.

The company has raised a large ($20m) seed round reflecting the excitement investors have in the technology, team and potential of the business. We are looking to build a world-class technology team to realise the extraordinary possibilities of what we are doing.

Applied Scientists at Unlikely AI, work the full project lifecycle: from literature to POC to production. You will have a key role in delivering products, starting with literature review, creating proof of concepts using cutting edge technology including the latest Machine Learning techniques, collaborating with colleagues to implement and test your ideas, and helping deliver your solutions to production. 

As a Principal Applied Scientist you will help in providing technical leadership within Applied Science and across the company. 

In addition to this, you will also:

- Convert cutting edge research into real products

- Design, build and experiment with cutting edge technologies

- Drive the design, development, and execution of scientific research projects

- Write software that is built and deployed in production systems

- Communicate complex solutions to colleagues

- Analyse & inspect large scale datasets

Required:

- 6+ years of hands-on experience in deep learning

- 2+ years of experience applying deep learning to NLP for example Large Language Models LLMs,Sequence to Sequence models such as Neuro - Machine Translation (NMT) and seq2seq parsers. 

- Experience utilising & deploying transformer models

- Deep knowledge of machine learning fundamentals

- Strong coding skills in Python, including the use of pytorch or tensorflow

- Enthusiasm to learn and get up to speed with cutting edge technologies which you may not already be deeply familiar with

- Strong verbal and written communication skills

- Cloud experience

- A clear track record of mentorship and coaching others

Desirable:

- Use of Python libraries that encourage best practice such as pytest, pylint, black etcML OpsDocker, K8s

- Start-up experience

- AWS

Please note this role is not a pure research role and does not involve the creation of academic literature, but you should be very comfortable with reading and utilising academic papers and applying these concepts in your work.